APPLICATION ARCHITECT L1

Job Description

Role: Senior AI/ML Engineer – Gen

AI & Cloud Solutions:

Location: Woodland Hills ,CA (onsite Role )

Key Responsibilities:

• Architect and Design: Lead the design of scalable, secure, and high-performance AI/ML systems leveraging Agentic Layer A2A frameworks and MCP Protocols.

• Solution Engineering: Drive end-to-end solution development including vector embeddings, prompt engineering, and context engineering for enterprise-grade GenAI applications.

• Cloud Deployment: Architect and oversee deployment of AI/ML workloads on Azure Cloud, ensuring compliance, scalability, and cost optimization.

• Data Architecture: Design and optimize data pipelines and storage solutions using Azure AI Search, Redis, Cosmos DB, Blob Storage, and Iceberg.

• Application Development: Build and manage Azure Functions and Azure Container Apps for microservices-based AI solutions.

• Performance & Scalability: Define cloud-native architecture patterns, implement performance tuning, and ensure resilience across distributed systems.

• Domain Expertise: Apply deep knowledge of healthcare domain requirements, ensuring solutions meet regulatory standards (HIPAA, GDPR, etc.) and handle sensitive data securely.

• Technical Leadership: Mentor engineering teams, establish best practices, and conduct design/code reviews.

• Innovation & Research: Stay ahead of emerging GenAI, LLM/NLM trends, and integrate cutting-edge approaches into enterprise solutions.

Required Skills & Expertise:

• Agentic Layer & Protocols: Hands-on expertise with Agentic Layer A2A frameworks and MCP Protocol for multi-agent orchestration.

• AI/ML Engineering: Strong background in vector embeddings, prompt engineering, context engineering, and fine-tuning LLMs.

• GenAI & LLM Concepts: Deep understanding of Generative AI, Natural Language Models (NLM), and Large Language Models (LLM).

• Programming: Advanced proficiency in Python; exposure to Java/Go is a plus.

• Cloud Proficiency: Strong experience with Azure Cloud services, including deployment, monitoring, and scaling.

• Databases: Expertise in Azure AI Search, Redis, Cosmos DB; familiarity with Blob Storage and Iceberg is advantageous.

• Cloud-Native Architecture: Solid grasp of microservices, containerization, serverless computing, scalability, and performance optimization.

• Healthcare Domain: Experience working with regulated data environments and compliance frameworks.